Models {Rtreemix} | R Documentation

## Functions for comparing the tree topologies of two mutagenetic trees mixture models

### Description

These functions implement a similarity measure for comparing the topologies of the trees of two mixture models `mixture1` and `mixture2`. `comp.models` chaaracterizes the similarity of the models based on sum of the number of different edges of matched tree components (similarity pairs). `comp.models.levels` quantifies the similarity of two mixture models by adding to the edge ddifference of each similarity pair in the previously described sum the L1 distance of the level vectors of the trees comprising the pair. A level vector can be associated to each tree component and denotes the depth of each of the genetic events in the tree. It is necessary that the two models have the same number of tree components build on the same number of genetic events. It is assumed that the mixtures have at least two tree components.

### Usage

    comp.models(mixture1, mixture2)
    comp.models.levels(mixture1, mixture2)

### Arguments

`mixture1` | An `RtreemixModel` object specifying the first component for the similarity calculation.
`mixture2` | An `RtreemixModel` object specifying the second component for the similarity calculation. The number of tree components equals the one of `mixture1`.

### Details

The value returned by the function `comp.models` is between 0 (no similarity) and 1 (identical models).

### Value

The functions return a numeric value that quantifies the similarity of the tree topologies of two mixture models.

### Author(s)

Jasmina Bogojeska

### See Also

`RtreemixModel-class`, `comp.trees`, `fit-methods`, `stability.sim`

### Examples

    ## Generate two random RtreemixModel objects each with 3 components.
    rand.mod1 <- generate(K = 3, no.events = 9, noise.tree = TRUE, prob =
    c(0.2, 0.8))
    rand.mod2 <- generate(K = 3, no.events = 9, noise.tree = TRUE, prob =
    c(0.2, 0.8))

    ## Compare the topologies of the tree components of the two randomly
    ## generated models
    comp.models(rand.mod1, rand.mod2)
    comp.models.levels(rand.mod1, rand.mod2)

[Package Rtreemix version 1.6.0 Index]